Zobrazeno 1 - 10
of 17 078
pro vyhledávání: '"Lipka A"'
Autor:
Owens, Deonna M., Rossi, Ryan A., Kim, Sungchul, Yu, Tong, Dernoncourt, Franck, Chen, Xiang, Zhang, Ruiyi, Gu, Jiuxiang, Deilamsalehy, Hanieh, Lipka, Nedim
Large Language Models (LLMs) are powerful tools with the potential to benefit society immensely, yet, they have demonstrated biases that perpetuate societal inequalities. Despite significant advancements in bias mitigation techniques using data augme
Externí odkaz:
http://arxiv.org/abs/2409.13884
Autor:
Lipka, Mathias, Thomas, Jens, Saglia, Roberto, Bender, Ralf, Fabricius, Maximilian, Partmann, Christian
We analyze the dark matter (DM) halos of a sample of dwarf Ellitpicals (dE) and discuss cosmological and evolutionary implications. Using orbit modeling we recover their density slopes and, for the first time, the halo flattening. We find the `cusp-c
Externí odkaz:
http://arxiv.org/abs/2409.11458
Autor:
Lipka, Mathias, Thomas, Jens, Saglia, Roberto, Bender, Ralf, Fabricius, Maximilian, Hill, Gary J., Kluge, Matthias, Landriau, Martin, Mazzalay, Ximena, Noyola, Eva, Parikh, Taniya, Snigula, Jan
We analyse the stellar structure of a sample of dwarf ellipticals (dE) inhabiting various environments within the Virgo cluster. Integral-field observations with a high spectral resolution allow us to robustly determine their low velocity dispersions
Externí odkaz:
http://arxiv.org/abs/2409.10518
We present a new approach for witnessing quantum resources, including entanglement and coherence, based on heat generation. Inspired by the concept of Maxwell's demon, we analyze the heat exchange between a quantum system and a thermal environment as
Externí odkaz:
http://arxiv.org/abs/2408.06418
Autor:
Aponte, Ryan, Rossi, Ryan A., Guo, Shunan, Dernoncourt, Franck, Yu, Tong, Chen, Xiang, Mitra, Subrata, Lipka, Nedim
Large language models (LLMs) have been applied to a wide range of tasks, including text summarization, web navigation, and chatbots. They have benefitted from supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) followin
Externí odkaz:
http://arxiv.org/abs/2408.02861
Autor:
Eppalapally, Swetha, Dangi, Daksh, Bhat, Chaithra, Gupta, Ankita, Zhang, Ruiyi, Agarwal, Shubham, Bagga, Karishma, Yoon, Seunghyun, Lipka, Nedim, Rossi, Ryan A., Dernoncourt, Franck
Question-answering for domain-specific applications has recently attracted much interest due to the latest advancements in large language models (LLMs). However, accurately assessing the performance of these applications remains a challenge, mainly d
Externí odkaz:
http://arxiv.org/abs/2407.16073
An extension of the xFitter open-source program for QCD analyses is presented, allowing for a polynomial parameterization of the dependence of physical observables on theoretical parameters. This extension enables simultaneous determination of parton
Externí odkaz:
http://arxiv.org/abs/2407.16061
Autor:
Lipka, Johannes B., Hans, Christian A.
In many state-of-the-art control approaches for power systems with storage units, an explicit model of the storage dynamics is required. With growing numbers of storage units, identifying these dynamics can be cumbersome. This paper employs recent da
Externí odkaz:
http://arxiv.org/abs/2407.05157
Autor:
Kumar, Ishita, Viswanathan, Snigdha, Yerra, Sushrita, Salemi, Alireza, Rossi, Ryan A., Dernoncourt, Franck, Deilamsalehy, Hanieh, Chen, Xiang, Zhang, Ruiyi, Agarwal, Shubham, Lipka, Nedim, Van Nguyen, Chein, Nguyen, Thien Huu, Zamani, Hamed
Long-text generation is seemingly ubiquitous in real-world applications of large language models such as generating an email or writing a review. Despite the fundamental importance and prevalence of long-text generation in many practical applications
Externí odkaz:
http://arxiv.org/abs/2407.11016
Aspect-Based Sentiment Analysis (ABSA) has experienced tremendous expansion and diversity due to various shared tasks spanning several languages and fields and organized via SemEval workshops and Germeval. Nonetheless, a few shortcomings still need t
Externí odkaz:
http://arxiv.org/abs/2405.20274